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Exact Fill Rates for the (R, S) Inventory Control with Discrete Distributed Demands for the Backordering Case

Author

Listed:
  • Eugenia BABILONI
  • Ester GUIJARRO
  • Manuel CARDÓS
  • Sofía ESTELLÉS

Abstract

The fill rate is usually computed by using the traditional approach, which calculates it as the complement of the quotient between the expected unfulfilled demand and the expected demand per replenishment cycle, instead of directly the expected fraction of fulfilled demand. Furthermore the available methods to estimate the fill rate apply only under specific demand conditions. This paper shows the research gap regarding the estimation procedures to compute the fill rate and suggests: (i) a new exact procedure to compute the traditional approximation for any discrete demand distribution; and (ii) a new method to compute the fill rate directly as the fraction of fulfilled demand for any discrete demand distribution. Simulation results show that the latter methods outperform the traditional approach, which underestimates the simulated fill rate, over different demand patterns. This paper focuses on the traditional periodic review, base stock system when backlogged demands are allowed.

Suggested Citation

  • Eugenia BABILONI & Ester GUIJARRO & Manuel CARDÓS & Sofía ESTELLÉS, 2012. "Exact Fill Rates for the (R, S) Inventory Control with Discrete Distributed Demands for the Backordering Case," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 16(3), pages 19-26.
    • Handle: RePEc:aes:infoec:v:16:y:2012:i:3:p:19-26
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    References listed on IDEAS

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    1. van der Heijden, Matthieu, 2000. "Near cost-optimal inventory control policies for divergent networks under fill rate constraints," International Journal of Production Economics, Elsevier, vol. 63(2), pages 161-179, January.
    2. Edward A. Silver, 1981. "Operations Research in Inventory Management: A Review and Critique," Operations Research, INFORMS, vol. 29(4), pages 628-645, August.
    3. Tempelmeier, Horst, 2007. "On the stochastic uncapacitated dynamic single-item lotsizing problem with service level constraints," European Journal of Operational Research, Elsevier, vol. 181(1), pages 184-194, August.
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